Four of fourteen models named Amazon Aurora first on the direct prompt; zero named Azure SQL Database. Amazon Aurora was named by thirteen of the fourteen models and Azure SQL Database by fourteen and Amazon Aurora carries 39 labels and Azure SQL Database 56, so the shares are not directly comparable.
Named in two categories this edition.
Named in two categories this edition.
Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all fourteen models, for a mid-market B2B company; rank is within the category; every quote names the model and the prompt it came from. Both figures come from the managed relational databases page.
Across every category in the October 2026 Edition, Amazon Aurora and Azure SQL Database were named in the same answer seventy-eight times, of the 107 answers naming Amazon Aurora and the 159 naming Azure SQL Database. In those answers Azure SQL Database took the first choice five times and Amazon Aurora twenty-three.
| Model | Direct | Paraphrase | Comparative | Budget-constrained | Scale-constrained | Negative |
|---|---|---|---|---|---|---|
| Claude Haiku 4.5 | ||||||
| GPT-5.4 mini | ||||||
| Gemini 3.5 Flash | ||||||
| Perplexity Sonar | ||||||
| Grok 4.1 Fast | ||||||
| Mistral Small | ||||||
| DeepSeek V4 Flash | ||||||
| Llama 4 Maverick | ||||||
| Qwen 3.7 Flash | ||||||
| Kimi K2 | ||||||
| GLM 4.7 FlashX | ||||||
| MiniMax M2.5 | ||||||
| GPT-6 Luna | ||||||
| Muse Glimmer 30B |
Bold names in an answer are the products the judge labeled a first choice; a model naming several gives each of them that label. The full answer text for every row is in the record.
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“Experts advise caution or avoidance for production environments where stable performance is critical.” Mistral Small · negative prompt · hard negative
“Aurora uses internal optimizations and sometimes proprietary features ... that can make migrating back to standard MySQL/Postgres difficult” Qwen 3.7 Flash · negative prompt · soft negative
“While Aurora is popular, be cautious about: Complex pricing - I/O charges can escalate unpredictably” Kimi K2 · negative prompt · soft negative
“a recommended hosted SQL database could be PostgreSQL with a cloud-managed service like AWS Aurora, as it balances capability, cost, and operational simplicity” Llama 4 Maverick · paraphrase prompt · first choice
“Pick AWS RDS/Aurora for broadest engine breadth and ecosystem maturity, and for cloud-native Aurora performance with MySQL/PostgreSQL compatibility.” Muse Glimmer 30B · comparative prompt · first choice
“is Amazon Relational Database Service (RDS) or Amazon Aurora, as they are fully managed relational database services” Llama 4 Maverick · direct prompt · first choice
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“Azure SQL Database, while generally robust, has resource caps and licensing implications that require careful planning” Mistral Small · negative prompt · soft negative
“Standard Azure SQL Database strips out many legacy features (like SSIS, SQL Agent jobs, and certain system views)” Qwen 3.7 Flash · negative prompt · soft negative
“These are solid managed services, but Azure's own guidance warns not to choose solely by engine compatibility” Perplexity Sonar · negative prompt · soft negative
“Azure SQL Database is a fully managed, intelligent relational database service built on the Microsoft SQL Server engine” Perplexity Sonar · comparative prompt · first choice
“Amazon RDS or Azure SQL Database would be the safest bets depending on your existing tech stack” MiniMax M2.5 · paraphrase prompt · first choice
“Best for Microsoft Shops ... Lower first-choice share (4%) in general recommendations, but very strong within Microsoft-centric environments” Kimi K2 · direct prompt · alternative
Comparisons are drawn for the top eight products in each category, each against each. The output is the models' output; nothing here is a recommendation by the index.